There is an extraction device that extracts patterns included in patterns of events represented by event data that have actually occurred. As an example of the event data, there is exemplified event data that represents patterns of events indicating information and answers of a respondent who has replied to one questionnaire. A description will now be made of a case in which the event data includes an event A that “the respondent to the questionnaire is male”, an event B that “the respondent to the questionnaire is aged in the thirties”, and an event C that “the answer to Question 1 of the questionnaire is ‘A1’”. In this case, the extraction device extracts the following patterns. The extraction device extracts, for example, a pattern of the event A, a pattern of the events A and B, a pattern of the events A, B, and C, a pattern of the event B, a pattern of the events B and C, and a pattern of the event C. Extracting these patterns with the extraction device allows a user of the extraction device to understand that the respondent who is male and aged in his thirties has given the reply “A1” to Question 1.
The following extraction device is an example of the extraction device described above. For example, an extraction device generates a child from a parent in an enumeration tree and determines whether the generated child occurs in patterns of events represented by event data that have actually occurred, and thus extracts a pattern included in the patterns of events represented by the event data that have actually occurred. Such an extraction device generates a child pattern by adding events to a parent pattern. The extraction device then uses the newly generated child pattern as a parent pattern to generate again a child pattern. In this manner, the extraction device repeats generation of a child pattern until a predetermined condition is satisfied. Conventional examples are described in Japanese Laid-open Patent Publication No. 04-125734 and Japanese Laid-open Patent Publication No. 2009-17340.
However, the above-described extraction device has a problem in that it fails to extract patterns efficiently. Specifically, such an extraction device generates a pattern that does not exist as an extracted pattern. A description will be made of a case in which, for example, the following event is added to the parent pattern in addition to the above-described events A, B, and C. Specifically, a description will be made of a case in which there are an event D that “the respondent to the questionnaire is female”, an event E that “the respondent to the questionnaire is aged in the twenties”, and an event F that “the answer to Question 1 of the questionnaire is ‘A2’”. In this case, the events A and D do not occur together in a pattern of events represented by the event data that represents the pattern of events indicating information and answers of a respondent who has replied to one questionnaire. That is because the sex of the respondent is either male or female. In addition, the events B and E do not occur together in such a pattern of events. That is because it is impossible to belong to both generations of the twenties and the thirties. Moreover, when Question 1 of the questionnaire is to be replied in the form of giving one answer, the events C and F do not occur together in such a pattern of events.
However, when a parent pattern includes the event A, the above-described extraction device generates a child pattern including the events A and D by adding the event D to the parent pattern. In the same way, when a parent pattern includes the event B, the above-described extraction device generates a child pattern including the events B and E by adding the event E to the parent pattern. When a parent pattern includes the event C, the above-described extraction device generates a child pattern including the events C and F by adding the event F to the parent pattern. In other words, the above-described extraction device generates patterns that include combinations of events that do not occur in events represented by event data, that is, mutually exclusive events. Although the patterns include the combinations of events that do not occur in the events represented by the event data, the above-described extraction device performs unnecessary processing of determining whether such patterns occur in the patterns of the events represented by the event data. This poses a problem in that the above-described extraction device fails to extract patterns efficiently.